code: def test_fit_and_transform_return_ordinal(self):
      # >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >>
      # returnOrd
      # >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >> >>
  
      fbt = FeatureBinarizerFromTrees(
          treeNum=1,
          treeDepth=3,
          returnOrd=True,
          colCateg=self.col_categorical,
          randomState=self.random_state,
      )
      fbt.fit(
          self.X_train[
              [
                  "mean area",
                  "mean concave points",
                  "cat num",
                  "cat alpha",
              ]
          ],
          self.y_train,
      )
      self.assertListEqual(
          fbt.ordinal, ["mean area", "mean concave points"]
      )
      self.assertTrue(type(fbt.scaler) is StandardScaler)
      self.assertTrue(
          fbt.scaler.transform(self.X_test[fbt.ordinal]).shape[1] == 2
      )
  
file_path: AIX360/tests/rbm/test_Feature_Binarizer_From_Trees.py
imports: from unittest import TestCase
  import numpy
  from numpy import ndarray
  from pandas import DataFrame
  from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from aix360.algorithms.rbm import FeatureBinarizerFromTrees
label_desc: Use image node_id 7 for calling the TestFeatureBinarizerFromTrees obj's underlying member method code with example usage: obj.test_fit_and_transform_return_ordinal() without return types